change to use lq results for plot

.gitignore

@@ -5,6 +5,10 @@
 # Files generated by invoking Julia with --track-allocation
 *.jl.mem
 
+merging_scenario_2_leadfilt*
+passing_scenario_2_leadfilt*
+mc_data*
+
 # System-specific files and directories generated by the BinaryProvider and BinDeps packages
 # They contain absolute paths specific to the host computer, and so should not be committed
 deps/deps.jl

derivations/Stackelberg_ILQGames_Writeup/stackelberg_ilqgames_writeup.tex

@@ -84,7 +84,7 @@ \section{Steps}
 
 At each iteration $k = 1, 2, \ldots$ until convergence condition $\| \Delta \gamma^i_{k} \| < $ threshold $\epsilon$,
 \begin{enumerate}
-\item Propagate $\gamma^i_{k-1}$ forward in time using the gain matrices $S^i_{1:T, k=i}$ from $\truestate{0}$ to get $\xi_k \equiv \{ \stackmeas{}{1:\horizon}, \ctrlhat{i}{1:\horizon} \}$.
+\item Propagate $\gamma^i_{k-1}$ forward in time using the gain matrices $S^i_{1:T, k=i}$ from $\truestate{0}$ to get $\state{k} \equiv \{ \stackmeas{}{1:\horizon}, \ctrlhat{i}{1:\horizon} \}$.
 
 \item Compute errors
 \[ \delta \truestate{t} = \truestate{t} - \stackmeas{}{1:\horizon}, ~~~ \delta \ctrl{i}{t} = \ctrl{i}{t} -  \ctrlhat{i}{1:\horizon}. \]

example/PassingScenario/CreateMergingScenarioGame.jl

@@ -104,16 +104,18 @@ function create_merging_scenario_costs(cfg::MergingScenarioConfig, si, w_p1, w_p
     c2b = PlayerCost(avoid_collisions_cost_fn, si)
 
     # 3. enforce speed limit and turning limit
-    c1c_i = AbsoluteLogBarrierCost(4, cfg.speed_limit_mps, false)
-    c1c_ii = AbsoluteLogBarrierCost(4, -cfg.speed_limit_mps, true)
+    reg_term = 100.
+    reg_offset = 0.01
+    c1c_i = AbsoluteLogBarrierCost(4, cfg.speed_limit_mps, false, reg_term, reg_offset)
+    c1c_ii = AbsoluteLogBarrierCost(4, -cfg.speed_limit_mps, true, reg_term, reg_offset)
 
-    c1c_iii = AbsoluteLogBarrierCost(3, cfg.θ₀+cfg.max_heading_deviation, false)
-    c1c_iv = AbsoluteLogBarrierCost(3, cfg.θ₀-cfg.max_heading_deviation, true)
+    c1c_iii = AbsoluteLogBarrierCost(3, cfg.θ₀+cfg.max_heading_deviation, false, reg_term, reg_offset)
+    c1c_iv = AbsoluteLogBarrierCost(3, cfg.θ₀-cfg.max_heading_deviation, true, reg_term, reg_offset)
 
-    c2c_i = AbsoluteLogBarrierCost(8, cfg.speed_limit_mps, false)
-    c2c_ii = AbsoluteLogBarrierCost(8, -cfg.speed_limit_mps, true)
-    c2c_iii = AbsoluteLogBarrierCost(7, cfg.θ₀+cfg.max_heading_deviation, false)
-    c2c_iv = AbsoluteLogBarrierCost(7, cfg.θ₀-cfg.max_heading_deviation, true)
+    c2c_i = AbsoluteLogBarrierCost(8, cfg.speed_limit_mps, false, reg_term, reg_offset)
+    c2c_ii = AbsoluteLogBarrierCost(8, -cfg.speed_limit_mps, true, reg_term, reg_offset)
+    c2c_iii = AbsoluteLogBarrierCost(7, cfg.θ₀+cfg.max_heading_deviation, false, reg_term, reg_offset)
+    c2c_iv = AbsoluteLogBarrierCost(7, cfg.θ₀-cfg.max_heading_deviation, true, reg_term, reg_offset)
 
     # 4, 5. minimize and bound control effort - acceleration should be easier than rotation
     c1de = QuadraticCost(zeros(8, 8), zeros(8), 0.)
@@ -125,20 +127,20 @@ function create_merging_scenario_costs(cfg::MergingScenarioConfig, si, w_p1, w_p
     max_rotvel = cfg.max_rotational_velocity_radps
     max_accel = cfg.max_acceleration_mps
 
-    c1de_i = AbsoluteLogBarrierControlCost(1, [1.; 0.], max_rotvel, false)
-    c1de_ii = AbsoluteLogBarrierControlCost(1, [1.; 0.], -max_rotvel, true)
-    c1de_iii = AbsoluteLogBarrierControlCost(1, [0.; 1.], max_accel, false)
-    c1de_iv = AbsoluteLogBarrierControlCost(1, [0.; 1.], -max_accel, true)
+    c1de_i = AbsoluteLogBarrierControlCost(1, [1.; 0.], max_rotvel, false, reg_term, reg_offset)
+    c1de_ii = AbsoluteLogBarrierControlCost(1, [1.; 0.], -max_rotvel, true, reg_term, reg_offset)
+    c1de_iii = AbsoluteLogBarrierControlCost(1, [0.; 1.], max_accel, false, reg_term, reg_offset)
+    c1de_iv = AbsoluteLogBarrierControlCost(1, [0.; 1.], -max_accel, true, reg_term, reg_offset)
 
     c2de = QuadraticCost(zeros(8, 8))
     R22 = [1. 0; 0 1.]
     add_control_cost!(c2de, 2, Z22)
     add_control_cost!(c2de, 1, Z22)
 
-    c2de_i = AbsoluteLogBarrierControlCost(2, [1.; 0.], max_rotvel, false)
-    c2de_ii = AbsoluteLogBarrierControlCost(2, [1.; 0.], -max_rotvel, true)
-    c2de_iii = AbsoluteLogBarrierControlCost(2, [0.; 1.], max_accel, false)
-    c2de_iv = AbsoluteLogBarrierControlCost(2, [0.; 1.], -max_accel, true)
+    c2de_i = AbsoluteLogBarrierControlCost(2, [1.; 0.], max_rotvel, false, reg_term, reg_offset)
+    c2de_ii = AbsoluteLogBarrierControlCost(2, [1.; 0.], -max_rotvel, true, reg_term, reg_offset)
+    c2de_iii = AbsoluteLogBarrierControlCost(2, [0.; 1.], max_accel, false, reg_term, reg_offset)
+    c2de_iv = AbsoluteLogBarrierControlCost(2, [0.; 1.], -max_accel, true, reg_term, reg_offset)
 
     # 6. log barriers on the x dimension ensure that the vehicles don't exit the road
     # TODO(hamzah) - remove assumption of straight road

example/PassingScenario/PassingScenarioPlotUtils.jl

@@ -37,11 +37,11 @@ function make_passing_scenario_pdf_plots(folder_name, snapshot_freq, cfg, limits
 
     # Only needs to be generated once.
     p1a = plot_leadership_filter_positions(sg_objs[1].dyn, rotated_true_xs[:, 1:T], rotated_x̂s[:, 1:T])
-    plot!(p1a, ylabel="Transverse Position (m)", xlabel="Along-Road Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
+    plot!(p1a, ylabel="Transverse Position (m)", xlabel="Longitudinal Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
     p1a = add_lane_lines!(p1a, cfg, limits)
 
     p1m = plot_leadership_filter_measurements(sg_objs[1].dyn, rotated_true_xs[:, 1:T], rotated_zs[:, 1:T])
-    plot!(p1m, ylabel="Transverse Position (m)", xlabel="Along-Road Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
+    plot!(p1m, ylabel="Transverse Position (m)", xlabel="Longitudinal Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
     p1m = add_lane_lines!(p1m, cfg, limits)
 
     pos_main_filepath = joinpath(folder_name, "LF_passing_scenario_main.pdf")
@@ -52,18 +52,20 @@ function make_passing_scenario_pdf_plots(folder_name, snapshot_freq, cfg, limits
 
     # Generate a probability plot no timings.
     prob_plot = make_probability_plots(times[1:T], probs[1:T])
-    plot!(prob_plot, title="")
+    plot!(prob_plot, title="Leadership Probability v. Time", xlabel="", ylabel="")
+    # plot!(prob_plot, leftmargin=10Plots.mm, bottommargin=10Plots.mm)
     prob_filepath = joinpath(folder_name, "LF_passing_scenario_probs.pdf")
     savefig(prob_plot, prob_filepath)
 
     ii = 1
     for t in iter1
         p1b = plot_leadership_filter_measurement_details(num_particles, sg_objs[t], rotated_true_xs[:, 1:T], rotated_x̂s; transform_particle_fn=rotate_particle_state, include_all_labels=true)
-        plot!(p1b,  ylabel="Transverse Position (m)", xlabel="Along-Road Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
+        plot!(p1b,  ylabel="Transverse Position (m)", xlabel="Longitudinal Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
         p1b = add_lane_lines!(p1b, cfg, limits)
 
         prob_plot = make_probability_plots(times[1:T], probs[1:T]; t_idx=t)
-        plot!(prob_plot, title="")
+        plot!(prob_plot, title="Leadership Probability v. Time", xlabel="", ylabel="")
+        # plot!(prob_plot, leftmargin=10Plots.mm, bottommargin=10Plots.mm)
 
         pos2_filepath = joinpath(folder_name, "0$(ii)_LF_passing_scenario_positions_detail.pdf")
         prob_filepath = joinpath(folder_name, "0$(ii)_LF_passing_scenario_probs.pdf")
@@ -90,12 +92,12 @@ function make_merging_scenario_pdf_plots(folder_name, snapshot_freq, cfg, limits
 
     # Only needs to be generated once.
     p1a = plot_leadership_filter_positions(sg_objs[1].dyn, rotated_true_xs[:, 1:T], rotated_x̂s[:, 1:T])
-    # plot!(p1a,  ylabel="Transverse Position (m)", xlabel="Along-Road Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
-    plot!(p1a,  ylabel="Transverse Position (m)", xlabel="Along-Road Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
+    # plot!(p1a,  ylabel="Transverse Position (m)", xlabel="Longitudinal Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
+    plot!(p1a,  ylabel="Transverse Position (m)", xlabel="Longitudinal Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
     p1a = add_lane_lines!(p1a, cfg, limits)
 
     p1m = plot_leadership_filter_measurements(sg_objs[1].dyn, rotated_true_xs[:, 1:T], rotated_zs[:, 1:T])
-    plot!(p1m, ylabel="Transverse Position (m)", xlabel="Along-Road Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
+    plot!(p1m, ylabel="Transverse Position (m)", xlabel="Longitudinal Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
     p1m = add_lane_lines!(p1m, cfg, limits)
 
     pos_main_filepath = joinpath(folder_name, "LF_merging_scenario_main.pdf")
@@ -106,18 +108,20 @@ function make_merging_scenario_pdf_plots(folder_name, snapshot_freq, cfg, limits
 
     # Generate a probability plot no timings.
     prob_plot = make_probability_plots(times[1:T], probs[1:T])
-    plot!(prob_plot, title="")
+    plot!(prob_plot, title="Leadership Probability v. Time", xlabel="", ylabel="")
+    # plot!(prob_plot, title="")
     prob_filepath = joinpath(folder_name, "LF_merging_scenario_probs.pdf")
     savefig(prob_plot, prob_filepath)
 
     ii = 1
     for t in iter1
         p1b = plot_leadership_filter_measurement_details(num_particles, sg_objs[t], rotated_true_xs[:, 1:T], rotated_x̂s; transform_particle_fn=rotate_particle_state, include_all_labels=true)
-        plot!(p1b, ylabel="Transverse Position (m)", xlabel="Along-Road Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
+        plot!(p1b, ylabel="Transverse Position (m)", xlabel="Longitudinal Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
         p1b = add_lane_lines!(p1b, cfg, limits)
 
         prob_plot = make_probability_plots(times[1:T], probs[1:T]; t_idx=t)
-        plot!(prob_plot, title="")
+        plot!(prob_plot, title="Leadership Probability v. Time", xlabel="", ylabel="")
+        # plot!(prob_plot, title="")
         # plot!(p6, title="")
 
         pos2_filepath = joinpath(folder_name, "0$(ii)_LF_merging_scenario_positions_detail.pdf")
@@ -147,7 +151,7 @@ function make_debug_gif(folder_name, filename, cfg, limits, dyn, horizon, times,
     # This plot need not be in the loop.
     title="x-y plot of agent positions over time"
     p1a = plot_leadership_filter_positions(dyn, rotated_true_xs[:, 1:T], rotated_x̂s[:, 1:T])
-    plot!(p1a, title=title,  ylabel="Transverse Position (m)", xlabel="Along-Road Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
+    plot!(p1a, title=title,  ylabel="Transverse Position (m)", xlabel="Longitudinal Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
     p1a = add_lane_lines!(p1a, cfg, limits)
 
     iter = ProgressBar(2:T)
@@ -156,7 +160,7 @@ function make_debug_gif(folder_name, filename, cfg, limits, dyn, horizon, times,
 
         plot_title = string("LF (", t, "/", T, "), Ts=", Ts, ", Ns=", num_particles, ", p(not transition)=", p_transition, ", #games: ", num_games)
         p1b = plot_leadership_filter_measurement_details(num_particles, sg_objs[t], rotated_true_xs[:, 1:T], rotated_x̂s[:, 1:T]; transform_particle_fn=rotate_particle_state, include_all_labels=true)
-        plot!(p1b,  ylabel="Transverse Position (m)", xlabel="Along-Road Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
+        plot!(p1b,  ylabel="Transverse Position (m)", xlabel="Longitudinal Position (m)", ylimit=(-(cfg.lane_width_m+1), cfg.lane_width_m+1), xlimit=limits_tuple)
         p1b = add_lane_lines!(p1b, cfg, limits)
 
         _, p_px, p_py, p_θ, p_v, _, _ = plot_states_and_controls(dyn, times[1:T], true_xs[:, 1:T], true_us)
@@ -175,7 +179,7 @@ function make_debug_gif(folder_name, filename, cfg, limits, dyn, horizon, times,
 
         # plot 4 - accel. controls
         title5 = "Input acceleration controls (u) over time"
-        p4 = plot( xlabel="t (s)", ylabel="accel. (m/s^2)", title=title5)
+        p4 = plot( xlabel="Time (s)", ylabel="accel. (m/s^2)", title=title5)
         plot!(p4, times[1:T], true_us[1][1, 1:T], label=L"\mathcal{A}_1 ω")
         plot!(p4, times[1:T], true_us[2][1, 1:T], label=L"\mathcal{A}_2 ω")
         plot!(p4, times[1:T], true_us[1][2, 1:T], label=L"\mathcal{A}_1 a")

example/PassingScenario/RunMergingScenario.jl

@@ -7,6 +7,7 @@ using Plots
 using ProgressBars
 using Random: MersenneTwister
 using Distributions: Bernoulli, MvNormal
+using Statistics
 #gr()
 
 include("CreateMergingScenarioGame.jl")
@@ -100,8 +101,10 @@ pos_unc = 1e-3
 vel_unc = 1e-3
 P₁ = Diagonal([pos_unc, pos_unc, θ_inc, vel_unc, pos_unc, pos_unc, θ_inc, vel_unc])
 
-# Process noise uncertainty
-Q = 1e-2 * Diagonal([1e-2, 1e-2, 1e-3, 1e-2, 1e-2, 1e-2, 1e-3, 1e-2])
+# Process noise uncertainty - P2 is leader, remember.
+pos_proc_1 = 1.5e-2
+pos_proc_2 = 1e-2
+Q = 1e-2 * Diagonal([pos_proc_1, pos_proc_1, 1e-3, 1e-2, pos_proc_2, pos_proc_2, 1e-3, 1e-2])
 
 
 # CONFIG: 
@@ -178,12 +181,19 @@ gr()
 folder_name = "merging_scenario_2_leadfilt_$(get_date_str())"
 isdir(folder_name) || mkdir(folder_name)
 
-# Generate the plots for the paper.
-snapshot_freq = Int((T - 1)/10)
-make_merging_scenario_pdf_plots(folder_name, snapshot_freq, cfg, limits, sg_objs[1].dyn, T, times, true_xs, true_us, probs, x̂s, zs, num_particles)
-# make_driving_scenario_pdf_plots(folder_name, snapshot_freq, cfg, limits, dyn, horizon, times, true_xs, true_us, probs, x̂s, zs, num_particles)
+# Timing
+mean_times_per_step = mean(iter_timings)
+std_times_per_step = std(iter_timings)
+println("merging iter timings $(mean_times_per_step)±$(std_times_per_step)")
 
-# This generates the gif.
-filename = "merging_scenario_2.gif"
-make_debug_gif(folder_name, filename, cfg, limits, dyn, T, times, true_xs, true_us, probs, x̂s, zs, Ts, num_particles, p_transition, num_games)
+# # Generate the plots for the paper.
+# snapshot_freq = Int((T - 1)/10)
+# make_merging_scenario_pdf_plots(folder_name, snapshot_freq, cfg, limits, sg_objs[1].dyn, T, times, true_xs, true_us, probs, x̂s, zs, num_particles)
+# # make_driving_scenario_pdf_plots(folder_name, snapshot_freq, cfg, limits, dyn, horizon, times, true_xs, true_us, probs, x̂s, zs, num_particles)
+
+# # # This generates the gif.
+# # filename = "merging_scenario_2.gif"
+# # make_debug_gif(folder_name, filename, cfg, limits, dyn, T, times, true_xs, true_us, probs, x̂s, zs, Ts, num_particles, p_transition, num_games)
+
+# println("Saved in $(folder_name).")
 

example/PassingScenario/RunPassingScenario2.jl

@@ -6,6 +6,7 @@ using LinearAlgebra: norm, Diagonal, I
 using ProgressBars
 using Random: MersenneTwister
 using Distributions: Bernoulli, MvNormal
+using Statistics
 
 include("CreatePassingScenarioGame.jl")
 include("GroundTruthUtils.jl")
@@ -146,13 +147,18 @@ x̂s, P̂s, probs, pf, sg_objs, iter_timings = leadership_filter(dyn, costs, t
 using Dates
 gr()
 
-# Create the folder if it doesn't exist
-folder_name = "passing_scenario_2_leadfilt_$(get_date_str())"
-isdir(folder_name) || mkdir(folder_name)
+# Timing
+mean_times_per_step = mean(iter_timings)
+std_times_per_step = std(iter_timings)
+println("passing iter timings $(mean_times_per_step)±$(std_times_per_step)")
 
-# Generate the plots for the paper.
-snapshot_freq = Int((T - 1)/10)
-make_passing_scenario_pdf_plots(folder_name, snapshot_freq, cfg, limits, sg_objs[1].dyn, T, times, true_xs, true_us, probs, x̂s, zs, num_particles)
+# # Create the folder if it doesn't exist
+# folder_name = "passing_scenario_2_leadfilt_$(get_date_str())"
+# isdir(folder_name) || mkdir(folder_name)
+
+# # Generate the plots for the paper.
+# snapshot_freq = Int((T - 1)/10)
+# make_passing_scenario_pdf_plots(folder_name, snapshot_freq, cfg, limits, sg_objs[1].dyn, T, times, true_xs, true_us, probs, x̂s, zs, num_particles)
 
 # # This generates the gif.
 # filename = "passing_scenario_2.gif"

example/SILQGamesExamples/ComputeTimingInfo.jl

@@ -6,12 +6,12 @@ using Statistics
 include("MCFileLocations.jl")
 
 
-lqp1_data_folder, s, lqp1_lf_path = get_final_lq_paths_p1()
+lqp1_data_folder, lqp1_silq_path, lqp1_lf_path = get_final_lq_paths_p1()
 # lqp2_data_folder, _, lqp2_lf_path = get_final_lq_paths_p2()
 # uqp1_data_folder, _, uqp1_lf_path = get_final_uq_paths_p1()
 nonlqp2_data_folder, nonlqp2_silq_path, nonlqp2_lf_path = get_final_nonlq_paths_p2()
 
-function compute_silqgames_timing_info(data_folder, silq_filename)
+function compute_silqgames_timing_info(data_folder, silq_filename; remove_build_times=false)
     mc_foldername = joinpath(mc_folder, data_folder)
     input_data_path = joinpath(mc_foldername, silq_filename)
     silq_data = load(input_data_path)["data"]
@@ -27,9 +27,17 @@ function compute_silqgames_timing_info(data_folder, silq_filename)
     mean_num_iters = mean(num_iterations .- 1)
     std_num_iters = std(num_iterations .- 1)
 
-    iteration_times = silq_data["elapsed_iteration_times"]
+    iteration_times = deepcopy(silq_data["elapsed_iteration_times"])
+
+    if remove_build_times
+        # For 100 sim LQ game, manually remove build times.
+        # println(iteration_times[1:5:100])
+        iteration_times[1:5:100] .= 0
+    end
     iters_of_interest = iteration_times[iteration_times[:] .!= 0]
-    @assert length(iters_of_interest)-silq_data["num_sims"] == sum(num_iterations.-1) "length 1: $(length(iters_of_interest)-silq_data["num_sims"]), length 2: $(sum(num_iterations.-1))"
+    if !remove_build_times
+        @assert length(iters_of_interest)-silq_data["num_sims"] == sum(num_iterations.-1) "length 1: $(length(iters_of_interest)-silq_data["num_sims"]), length 2: $(sum(num_iterations.-1))"
+    end
 
     mean_iter_time = mean(iters_of_interest)
     std_iter_time = std(iters_of_interest)
@@ -74,17 +82,21 @@ function compute_overall_timing_info(data_folder, lf_filename)
 end
 
 # LQ P1
-lq1_lf_m, lq1_lf_s, lq1_silq_m, lq1_silq_s = compute_overall_timing_info(lqp1_data_folder, lqp1_lf_path)
-println("LQ SILQGames (P1), 201 timesteps @ 0.05s: $(lq1_silq_m) ± $(lq1_silq_s)")
-println("LQ LF (P1), 201 timesteps @ 0.05s, Ts=30, Ns=50: $(lq1_lf_m) ± $(lq1_lf_s)")
+# lq1_lf_m, lq1_lf_s, lq1_silq_m, lq1_silq_s = compute_overall_timing_info(lqp1_data_folder, lqp1_lf_path)
+# println("LQ SILQGames (P1), 501 timesteps @ 0.02s: $(lq1_silq_m) ± $(lq1_silq_s)")
+# println("LQ LF (P1), 501 timesteps @ 0.05s, Ts=75, Ns=50: $(lq1_lf_m) ± $(lq1_lf_s)")
 
-# # LQ P1
+# Non-LQ P1
 # nonlq2_lf_m, nonlq2_lf_s, nonlq2_silq_m, nonlq2_silq_s = compute_overall_timing_info(nonlqp2_data_folder, nonlqp2_lf_path)
-# println("NonLQ SILQGames (P2), 251 timesteps @ 0.02s: $(nonlq2_silq_m) ± $(nonlq2_silq_s)")
+# println("NonLQ SILQGames (P2), 501 timesteps @ 0.02s: $(nonlq2_silq_m) ± $(nonlq2_silq_s)")
 # println("NonLQ LF (P2), 251 timesteps @ 0.02s, Ts=30, Ns=100: $(nonlq2_lf_m) ± $(nonlq2_lf_s)")
 
 
-lq_iters_mean, lq_iters_std, lq_iter_time_mean, lq_iter_time_std = compute_silqgames_timing_info(lqp1_data_folder, lqp1_silq_path)
+lq_iters_mean, lq_iters_std, lq_iter_time_mean, lq_iter_time_std = compute_silqgames_timing_info(lqp1_data_folder, lqp1_silq_path; remove_build_times=true)
 lq_lf_iters_means, lq_lf_iters_stds, lq_lf_total_mean, lq_lf_total_std = compute_leadership_filter_timing_info(lqp1_data_folder, lqp1_lf_path)
+println("LQ SILQGames (L=P2) 501 timesteps @ 0.02s: time/iteration: $(lq_iter_time_mean) ± $(lq_iter_time_std) \niterations: $(lq_iters_mean) ± $(lq_iters_std)")
+println("LQ SLF (L=P2) 501 timesteps @ 0.02s, Ts=75, Ns=50: time/iteration: $(mean(lq_lf_iters_means)) ± $(mean(lq_lf_iters_stds)) \nTotal Time: $(lq_lf_total_mean) ± $(lq_lf_total_std)")
 
+# For non-LQ paper timing metrics.
 nonlq_iters_mean, nonlq_iters_std, nonlq_iter_time_mean, nonlq_iter_time_std = compute_silqgames_timing_info(nonlqp2_data_folder, nonlqp2_silq_path)
+println("Non-LQ SILQGames (L=P2) 501 timesteps @ 0.02s: time/iteration: $(nonlq_iter_time_mean) ± $(nonlq_iter_time_std) \niterations: $(nonlq_iters_mean) ± $(nonlq_iters_std)")